1. Field of the Invention
This invention relates generally to processing information from a received signal and, more particularly, to increasing range resolution in a LADAR system.
2. Description of the Related Art
Once common application for laser technology is laser detecting and ranging (LADAR) systems. In LADAR systems, brief laser pulses are generated and transmitted via a scanning mechanism. Some of the transmitted pulses striking a target of interest are reflected back to a receiver associated with the transmitter. The time between the transmission of a laser pulse and the receipt of the reflected laser pulse ("return pulse") is used to calculate the "range" from the object that reflected the laser pulse to the object that receives the return pulse.
There are several types of known LADAR systems. In one type, electronic circuitry begins a ramp function concurrently with the transmission of the outgoing pulse. The ramp function halts when the return pulse is received. Thus, the height of the resulting ramp is directly proportional to the range to the target. In a second type, a counter starts when a laser pulse is transmitted and terminates the counter when the return pulse is detected. The value of the counter is thus proportional to the distance to the target. Both of these types suffer from threshold uncertainties and a variety of other problems. In response to these problems, a third type of LADAR system was developed. Exemplary of this third type of LADAR system is the one disclosed in my U.S. Pat. No. 5,357,331, entitled "System for Processing Reflected Energy Signals," and issued Oct. 18, 1994, to what is now Lockheed Martin Corporation as my assignee.
This particular LADAR system employs a digital filter, known as a finite impulse response ("FIR") filter, for signal correlation and signal convolution in the course of extracting range information from digital samples of the return pulse. Technically, the FIR filter is a discrete linear time-invariant system having an output based on the weighted summation of a finite number of past inputs. A FIR filter performs a convolution, or convolves, the digitized samples from the received pulse with another signal. In this case, FIR filter convolves the digitized samples with a signal embodying a set of predetermined coefficients expected to describe the return pulse. The coefficient signal, consequently known as a "template."
The result of the convolution is a measure of correlation between the reflected signal and the template. Correlation is a technique widely used to determine the similarity or dissimilarity between two signals. Two identical signals will have a maximum positive correlation; a signal will have a maximum negative correlation with its polar opposite; and a signal will have a zero or negligible correlation with a totally dissimilar function. The LADAR system can determine the time of the return pulse by determining which set of digitized samples have the highest correlation to the template. From the arrival time and the transmission time, the LADAR system then calculates the range.
Convolution, in the context discussed above, involves the physical manipulation of two signals to determine their similarity. Like many things in nature, the convolution can be mathematically described and, more particularly, can be described by Equation 1: ##EQU1## As reflected in Equation 1, the convolution requires N multiply-and-accumulate operations for each sample of Cxy(m), where N is the number of convolution points having a size dependent upon the duration of the two signals or their periodicity if they are periodic. The parameters "k" and "m" index the sample points of the respective input signals. Since correlation is a particular class of convolution, the same is true for correlation.
For real time applications in which signals are processed as they are received, data processing including convolutions must occur very quickly. More specifically, the system must perform the convolutions calculations fast enough to accommodate the Nyquist rate (over two times the bandwidth of the sampled signal). As stated above, each sample Cxy(m) requires N multiply-and-accumulate operations. This is because the summation must be calculated for every value of k, from (k=0) through (k=(N-1)). In a system designed to process signals having frequencies up to 50 MHz, for example, the sampling rate (Nyquist rate) must be at least 100 MHz (100 mega-samples/second) which corresponds to a period of 10 nsec. This means that the system has 10 nsec to accomplish N multiply-and-accumulate operations. If N is equal to ten (meaning that the filter function is ten samples wide) then each of the ten multiply-and-accumulate operations must be accomplished in 1 nsec. This would be a formidable task for even modern day electronics.
In designing LADAR systems, engineers are also typically concerned with increasing the resolution afforded by such systems. One way to increase range resolution is to increase the frequency of the LADAR pulses emitted by the system. In systems that utilize the time between LADAR pulses to analyze return pulses, increasing the frequency of the pulses requires that the analysis of the return pulses be conducted more quickly. Another way is to increase the sampling rate at which the, analog return pulse is digitized for processing. However, this technique is typically limited by hardware whose operational speed constrains the sampling rate. Further, both these approaches to increasing resolution increase the time pressure on performing the convolution, either by reducing the amount of time in which the given convolutions must take place or by increasing the amount of convolution that must occur in the given amount of time.
The present invention is directed to overcoming, or at least reducing the effects of, one or more of the problems set forth above.